Re: st: Query..

[John Antonakis <John.Antonakis@unil.ch>]

In general I find Acock's books helpful and I have bought two of them. 
The latest one he has on SEM was gives a very nice overview of the SEM 
module in Stata. However, it is disappointing on some of the statistical 
theory, in particular with respect to fact that he gave too much 
coverage to "approximate" indexes of overidentification, which are not 
tests, and did not explain enough what the chi-square statistic of 
overidentification is.

The Stata people are usually very good about strictly following 
statistical theory, as do all econometricians, and do not promote too 
much these approximate indexes.  So, I was a bit annoyed to see how much 
airtime was given to rule-of-thumb indexes that have no known 
distributions and are not tests. The only serious test of 
overidentification, analogous to the Hansen-Sargen statistic is the 
chi-square test of fit. So, my suggestion to Alan is that he spends some 
time to cover that in the updated addition and not to suggest that 
models that fail the chi-square test are "approximately good."

For those who do not know what this statistic does, it basically 
compares the observed variance-covariance (S) matrix to the fitted 
variance covariance matrix (sigma) to see if the difference (residuals) 
are simultaneously different from zero. The fitting function that is 
minimized is:

Fml =  ln|Sigma| - ln|S| + trace[S.Sigma^-1] - p

As Sigma approaches S, the log of the determinant of Sigma less the log 
of the determinant of S approach zero; as concerns the two last terms, 
as Sigma approaches S, the inverse of Sigma premultiplied by S makes an 
identity matrix, whose trace will equal the number of observed variables 
p (thus, those two terms also approach zero). The chi-square statistic 
is simply Fml*N, at the relevant DF (which is elements in the 
variance-covariance matrix less parameters estimated).

This chi-square test will not reject a correctly specified model; 
however, it does not behave as expected at small samples, when data are 
not multivariate normal, when the model is complex (and the n to 
parameters estimated ration is low), which is why several corrections 
have been shown to better approximate the true chi-square distribution 
(e.g., Swain correction, Yuan-Bentler correction, Bollen-Stine bootstrap).

In all, I am thankful to Alan for his nice "how-to" guides which are 
very helpful to students who do not know Stata need a "gentle 
introduction"--so I recommend them to my students, that is for sure. 
But, I would appreciate a bit more beef from him for the SEM book in 
updated versions.

Best,
J.

__________________________________________

John Antonakis
Professor of Organizational Behavior
Director, Ph.D. Program in Management

Faculty of Business and Economics
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland
Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305
http://www.hec.unil.ch/people/jantonakis

Associate Editor
The Leadership Quarterly
__________________________________________

On 16.04.2013 17:45, Lachenbruch, Peter wrote:
> David -
> It would be good for you to specify what you find problematic with 
Acock's book.  I've used it and not had any problems - but maybe i'm 
just ancient and not seeing issues
>
> Peter A. Lachenbruch,
> Professor (retired)
> ________________________________________
> From: owner-statalist@hsphsun2.harvard.edu 
[owner-statalist@hsphsun2.harvard.edu] on behalf of Hutagalung, Robert 
[Robert.Hutagalung@med.uni-jena.de]
> Sent: Monday, April 15, 2013 2:06 AM
> To: statalist@hsphsun2.harvard.edu
> Subject: AW: st: Query..
>
> Hi David,
> Thanks, though I find the book very useful.
> Best, Rob
>
> -----Ursprüngliche Nachricht-----
> Von: owner-statalist@hsphsun2.harvard.edu 
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von David Hoaglin
> Gesendet: Samstag, 13. April 2013 16:11
> An: statalist@hsphsun2.harvard.edu
> Betreff: Re: st: Query..
>
> Hi, Rob.
>
> I am not able to suggest a book on pharmacokinetics/pharmacodynamics,
> but I do have a comment on A Gentle Introduction to Stata.  As a 
statistician, I found it helpful in learning to use Stata, but a number 
of its explanations of statistics are very worrisome.
>
> David Hoaglin
>
> On Fri, Apr 12, 2013 at 9:01 AM, Hutagalung, Robert 
<Robert.Hutagalung@med.uni-jena.de> wrote:
>> Hi everyone, I am a new fellow here..
>> I am wondering if somebody could  a book (or books) on Stata dealing 
with pharmacokinetics/pharmacodinamics - both analyses and graphs.
>> I already have: A Visual Guide to Stata Graphics, 2' Edition, A 
Gentle Introduction to Stata, Third Edition, An Introduction to Stata 
for Health Researchers, Third Edition.
>> Thanks in advance, Rob.
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